@article {Liunavi.502, author = {Xingjie Liu and Guolei Wang, and Ken Chen}, title = {High-Precision Vision Localization System for Autonomous Guided Vehicles in Dusty Industrial Environments}, volume = {69}, number = {1}, elocation-id = {navi.502}, year = {2022}, doi = {10.33012/navi.502}, publisher = {Institute of Navigation}, abstract = {Ensuring a convenient yet accurate localization solution is an essential problem in wireless-denied industrial scenarios. Therefore, in this study, a vision localization system with light emitting diode (LED) array targets for autonomous guided vehicle (AGV) navigation is proposed. The visible targets are calibrated and the pose can be computed using a camera that views the LED target. A novel data filtering method that integrates the odometer data and inertial measurement unit (IMU) data with vision data is introduced to provide stable and accurate localization. The vision localization system was tested on a 5-m-long AGV and the results demonstrated that the proposed system obtained a static position accuracy at 6 mm, kinematic position accuracy at 10 mm, and angle accuracy at 0.052{\textdegree}, which is more precise than the other methods used in industrial AGV applications.}, issn = {0028-1522}, URL = {https://navi.ion.org/content/69/1/navi.502}, eprint = {https://navi.ion.org/content/69/1/navi.502.full.pdf}, journal = {NAVIGATION: Journal of the Institute of Navigation} }